Estimation of Mortality Rate of COVID-19 in India using SEIRD Model

Dharmaraja Selvamuthu (), Deepak Khichar, Priyanka Kalita and Vidyottama Jain ()
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Dharmaraja Selvamuthu: Indian Institute of Technology Delhi
Deepak Khichar: Indian Institute of Technology Delhi
Priyanka Kalita: Indian Institute of Technology Delhi
Vidyottama Jain: Central University of Rajasthan

OPSEARCH, 2023, vol. 60, issue 1, No 21, 539-553

Abstract: Abstract In India, the number of infections is rapidly increased with a mounting death toll during the second wave of Coronavirus disease (COVID-19). To measure the severity of the said disease, the mortality rate plays an important role. In this research work, the mortality rate of COVID-19 is estimated by using the Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) epidemiological model. As the disease contains a significant amount of uncertainty, a fundamental SEIRD model with minimal assumptions is employed. Further, a basic method is proposed to obtain time-dependent estimations of the parameters of the SEIRD model by using historical data. From our proposed model and with the predictive analysis, it is expected that the infection may go rise in the month of May-2021 and the mortality rate could go as high as 1.8%. Such high rates of mortality may be used as a measure to understand the severity of the situation.

Keywords: COVID-19; SEIRD model; Mortality rate; Parameter estimation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12597-021-00557-x

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